K Eswaramoorthy
@nrcmec.org
Associate Professor and Department of Electrical & Electronics Engineering
Narsimha Reddy Engineering College
RESEARCH INTERESTS
Power Electronics and Drives,power quality, electrical vehicle , renewable energy
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
T. Abhishek, Dola Sundeep, C. Chandrasekhara Sastry, K. V. Eswaramoorthy, Gagan Chaitanya Kesireddy, Bobbili Veera Siva Reddy, Rakesh Kumar Verma, Sachin Salunkhe, Robert Cep, and Emad Abouel Nasr
Frontiers Media SA
Introduction:The demand for improved small arms ammunition has led to exploring advanced materials and manufacturing techniques. This research investigates the machining characteristics of CM and WNF alloy bullets, aiming to enhance ballistic performance and durability.Methods:Bullet profile-making trials were conducted to evaluate the impact of machining parameters such as cutting speed and feed. The study also considered variables including surface roughness, cutting temperature, and hardness, alongside a detailed morphological analysis, The evaluation utilized an orthogonal array and MCDM approach, incorporating the TOPSIS method for decision-making processes.Results:The findings reveal that WNF alloy bullets exhibit 3.01% to 27.95% lower machining temperatures, 24.88%-61.85% reduced surface roughness, and 19.45%-34% higher microhardness compared to CM bullets. Moreover, CM bullets demonstrated higher machining temperatures, resulting in 47.53% increased tool flank wear. WNF bullets showed a 24.89% reduction in crater wear and a 38.23% decrease in compressive residual stress in bullet profiles, indicating superior machining performance.Discussion:The superior machining performance of WNF alloy bullets suggests their potential to improve the ballistic performance and durability of small arms ammunition. The reduced tool wear and favorable machining parameters highlight WNF alloy's advantages for military and defense applications. A ballistic impact analysis using a finite element method (FEM) model in Abaqus software further supports the potential of WNF alloy bullets, providing a solid foundation for future advancements in bullet manufacturing technologies.
B. Sendhil Nathan, B. Veera Siva Reddy, C. Chandrasekhara Sastry, J. Krishnaiah, and K. V. Eswaramoorthy
Frontiers Media SA
Effective service parts management and demand forecasting are crucial for optimizing operations in the automotive industry. However, existing literature lacks a comprehensive framework tailored to the specific context of the Thai automotive sector. This study addresses this gap by proposing a strategic approach to service parts management and demand forecasting in the Thai automotive industry. Drawing on a diverse set of methodologies, including classical time series models and advanced machine learning techniques, various forecasting models were assessed to identify the most effective approach for predicting service parts demand. Categorization of service parts based on demand criteria was conducted, and decision rules were developed to guide stocking strategies, balancing the need to minimize service disruptions with cost optimization. This analysis reveals substantial cost savings potential through strategic stocking guided by the developed decision rules. Furthermore, evaluation of the performance of different forecasting models recommends the adoption of Support Vector Regressor (SVR) as the most accurate model for forecasting service parts demand in this context. This research contributes to the automotive service industry by providing a nuanced framework for service parts management and demand forecasting, leading to cost-effective operations and enhanced service quality. The findings offer valuable insights for practitioners and policymakers seeking to improve efficiency and sustainability in the Thai automotive sector.
Dola Sundeep, Eswaramoorthy KV, Bandlamudi Tanmayi, M Sai Supriya, and Giridhar Madagani
IEEE
This paper presents the development of an innovative Remote Triggered Laboratory (RTL) that enables remote characterization of analog components. Designed for the current era of online learning, the RTL, accessed via a web interface, provides a safe, efficient, and user-friendly approach for students to conduct experiments outside a traditional lab environment. This system focuses on the characterization of diodes, Bipolar Junction Transistors (BJTs), and Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs). The setup incorporates relay modules and a PC connected through a USB interface. It employs Python-based software and an Arduino Mega controller, ensuring efficient execution and ease of use. The RTL also ensures safety by limiting user operation to prevent potentially dangerous situations. This advancement in remote labs opens up unrestricted experimental opportunities for students, improving accessibility and advancing the educational experience in semiconductor device characterization.
Muthukumar Paramasivan, K. Eswaramoorthy, Rathinam Muniraj, Padmasuresh Lekshmi Kanthan, Thanikanti Sudhakar Babu, S. Jeevananthan, and Hassan Haes Alhelou
Institute of Electrical and Electronics Engineers (IEEE)
This paper suggests an alternate level enhancing algorithm to operate the nine-level cascaded multilevel inverter (CHBMLI) for a 31-level output, which involves an inventive selection of optimal asymmetrical voltage values in separate DC sources (SDCs) and a quarter-wave symmetry pulse pattern pulse width modulation (QSP-PWM). The symmetrical CHBMLI structure involves the same DCs with an objectionable value of component count, especially at higher level outputs; consequently, there is a need to reduce the component count. It can be supported largely by the optimal set of asymmetrical voltage values (say 1:2:4:8), such an actualization is quite easy with photovoltaic (PV) applications. Additionally, many of the commonly used PWM methods of MLI are tedious especially when it comes to the generation of pulses. This paper also engraves a straightforward switching strategy apposite to the developed MLI topology. In addition, three new switching angle modulation schemes have been proposed to get the optimum performance, namely, incremental delay switching angle modulation scheme, random delay switching angle modulation scheme and sine referencing-based switching angle modulation scheme. The preliminary study on the tenet of suggested topology is done theoretically, then the performance is analyzed in MATLAB2019a software and finally, experimentally corroborated on a proof-of-concept (POC) prototype with the aid of ModelSim6.3f hardware description language simulation environment, Xilinx 14.5 project navigator tool and XC3S500E field-programmable-gate-array processor. The tested results for the inductive load demonstrate the output voltage synthesizing and the total harmonic distortion curtailment savvies of the proposed MLI and the switching strategies.
Lekshmi Sree B, A. Sangari, Eswaramoorthy K, Kiranmayee V, J. Anto Sheeba, and D. Sivamani
IEEE
One of the most vital and expensive components of electric vehicles is the battery. Of course, the battery is the only source of electricity for an electric vehicle. However, the vehicle's power supply eventually declines, resulting in decreased performance. For battery manufacturers, this is a major concern. In this paper, it is proposed to use IoT approaches to monitor and display the battery performance. Here, the various battery metrics, including voltage, current, and temperature, are tracked, observed, and shown. This alerts the user to prevent the battery from being overcharged or deeply discharged. With the use of various sensors, observation can be carried out. Data on voltage, current, and temperature are sent to a microcontroller unit, which subsequently transmits battery data via the cloud for display. Real-time data of voltage, current, and temperature may be displayed by the monitoring system, and the data can be seen on an Android smartphone and a computer at the same time. As a result, we might be able to improve the battery's efficiency and lifespan. The user interface and results presentation are the two main components of the proposed IoT -based battery monitoring system. According to test results, the system is able to recognize weakened battery performance and notifies the user for further action.
Dhineshkumar Krishnan, G Prakash, N Vengadachalam, R Amaleswari, and K. Eswaramoorthy
IEEE
The Multi-Level Inverters (MLI) are paid wider attraction to develop stepped voltage profile imitation sinusoidal and miserable Total Harmonic Distortion (THD). Many normal geometries are suggested to understand MLI; even so, the drawbacks of those same architectures could include so much Voltage levels and electricity equipment, as well as lower THD, that either raises both the cost and magnitude of the system. To help with cutting edge flow studies in this theme and in the choice of reasonable inverter at different presentations. By using n of these sections, both recommended MLI architecture, i.e., PS1 as well as PS2, may integrated 4n+5 and 4n+7 levels, independently at the produce but instead of 2n+3 levels with solely RSHB MLI. The dual distributed energy resources employed in the systems.
P. Muthukumar, Venkata Ramesh Maddukuri, K. Eswaramoorthy, N. Veeramuthulingam, and T. Jarin
Inderscience Publishers
P. Muthukumar, L. Padmasuresh, K. Eswaramoorthy, and S. Jeevananthan
Springer Science and Business Media LLC
P. Muthukumar, Padma Suresh Lekshmi Kanthan, T. Baldwin Immanuel, and K. Eswaramoorthy
Springer Singapore